T06: Emerging Technologies Supported by Big Data Analytics in Education

 

Topics

Big data analytics in education, as an emerging topic in the agenda of educational technology research, has been frequently associated with the opportunities and the challenges of the so-called Big Data in today's networked world. The former touches upon the affordances of Big Data Analytics in education, such as: the prediction of at-risk students, the provision of real-time feedback on students' performance, recommendations of appropriate learning activities or courses, and recommendations on student group formation. The latter touches upon issues related to the storage, analysis and reporting of the big data, including the associated ethical concerns such as privacy violations.

The aim of this track is to further promote the discussion on both the opportunities and the challenges that arise from leveraging Big Data Analytics in Education among researchers, practitioners and policy makers alike. The topic is multifaceted and complex, since different aspects, such as pedagogy, technology, and policy, can interplay. In addition, it can be viewed at various levels: micro-level (e.g. individual student or group of students), meso-level (e.g. the school or the university) or macro-level (e.g. regional, local, national). Most importantly, it seems that this data-driven culture in education which is still in its infancy has the potential of affecting fundamental aspects of learning (e.g. student feedback), the educational processes and practices, as well as our educational policy and our governance systems.

Topics include (but are not limited to):

  • Applications for formal or informal learning
  • Innovative techniques
  • Methodological issues or innovative methods
  • Theoretical considerations
  • Ethical concerns
  • The interplay of learning design and big data analytics
  • Policy-related aspects
  • Systematic reviews or mapping studies
Track Co-Chairs
  • Hui-Chun Hung, Taipei Medical University, Taiwan
  • Anna Mavroudi, KTH Royal Institute of Technology, Sweden
  • POON Kin Man Leonard, The Education University of Hong Kong, Hong Kong
Program Committee
  • Zacharoula Papamitsiou, Norwegian University of Science and Technology, Norway
  • Tharrenos Bratitsis, University of Western Macedonia, Greece
  • Pau Libbrecht, Leibniz Institute for Research and Information in Education, Germany
  • Thrasyvoulos Tsiatsos, Aristotle University of Thessaloniki, Greece
  • Huei-Tse Hou, National taiwan university of science and technology, Taiwan
  • Jiun-Yu Wu, National Chiao Tung University, Taiwan
  • Shu-Ming Wang, Chinese Culture University, Taiwan
  • Yu-Sheng Su, National Taiwan Ocean University, Taiwan
  • Zhourong Chen, Hong Kong University of Science and Technology

 

Paper submission: https://easychair.org/conferences/?conf=sete2019